Systems and methods for dropping data using a drop profile

ABSTRACT

A system selectively drops data from queues. The system includes a drop table that stores drop probabilities. The system selects one of the queues to examine and generates an index into the drop table to identify one of the drop probabilities for the examined queue. The system then determines whether to drop data from the examined queue based on the identified drop probability.

RELATED APPLICATION

This application claims priority under 35 U.S.C. § 119 based on U.S.Provisional Application No. 60/350,985, filed Jan. 25, 2002, thedisclosure of which is incorporated herein by reference.

BACKGROUND OF THE INVENTION

1. Field of the Invention

The present invention relates generally to congestion control duringdata transfer and, more particularly, to systems and methods fordropping data using a drop profile.

2. Description of Related Art

Conventional network devices, such as routers, relay streams of datathrough a network from a source to a destination. Typically, the networkdevices include one or more memory subsystems to temporarily buffer datawhile the network devices perform network-related functions, such asroute processing or accounting.

A data stream may be considered a pipe of data packets belonging to acommunication between a particular source and a particular destination.A network device may assign a variable number of queues (e.g., where aqueue may be considered a logical first-in, first-out (FIFO) buffer) toa data stream. For a stream with n queues, the relationship of queuesand streams may be represented by:

${stream}_{bandwidth} = {\sum\limits_{0}^{n - 1}\;{{queue}_{bandwidth}.}}$

A problem that may arise in the use of queues is that congestion occursif data builds up too quickly in the queues (i.e., data is enqueued at afaster rate than it is dequeued). Network devices typically address thisproblem by notifying sources of the packets of the congestion. Thisnotification sometimes takes the form of dropping more recent packetsreceived from the sources. It is sometimes a difficult andtime-consuming process, however, to decide whether to drop a packet froma queue.

Therefore, there is a need for efficient mechanisms for determiningwhether to drop data from a queue.

SUMMARY OF THE INVENTION

Systems and method consistent with the principles of the inventionaddress this and other needs by using a drop profile to determinewhether to drop data from a queue. The drop profile may differ fordifferent data streams and possibly for different data in the same datastream.

In accordance with the principles of the invention as embodied andbroadly described herein, a system selectively drops data from queues.The system includes a drop table that stores drop probabilities. Thesystem selects one of the queues to examine and generates an index intothe drop table to identify one of the drop probabilities for theexamined queue. The system then determines whether to drop data from theexamined queue based on the identified drop probability.

In another implementation consistent with the principles of theinvention, a network device includes groups of queues and drop enginescorresponding to the queue groups. Each of the queue groups correspondsto a data stream. Each of the drop engines selects one of the queues toexamine, identifies a drop probability for data in the selected queue,and determines whether to drop data from the selected queue based on theidentified drop probability.

In yet another implementation consistent with the principles of theinvention, a method for selectively dropping data from queues thattemporarily store data includes selecting one of the queues to examine;identifying a drop probability for data in the examined queue; comparingthe drop probability to a random number; and determining whether to dropthe data from the examined queue based on a result of the comparison.

In a further implementation consistent with the principles of theinvention, a system selectively drops data from queues. The systemincludes queues that temporarily store data and a drop engine. The dropengine selects one of the queues to examine, determines a static amountof memory allocated to the selected queue, determines an amount ofmemory used by the selected queue, identifies a drop probability fordata in the selected queue based on the static amount of memoryallocated to the selected queue and the amount of memory used by theselected queue, and determines whether to drop the data from theselected queue based on the identified drop probability.

In another implementation consistent with the principles of theinvention, a drop engine selectively drops data from multiple queues.The drop engine includes drop tables, indexing logic, and drop decisionlogic. Each of the drop tables is configured to store multiple dropprobabilities. The indexing logic is configured to select one of thedrop tables and generate an index into the selected drop table toidentify one of the drop probabilities. The drop decision logic isconfigured to determine whether to drop data from one of the queuesbased on the identified drop probability.

In a further implementation consistent with the principles of theinvention, a drop engine selectively drops data from multiple queues.The drop engine includes a drop table, indexing logic, and drop decisionlogic. The drop table is configured to store multiple dropprobabilities. The indexing logic is configured to generate an indexinto the drop table to identify one of the drop probabilities. The dropdecision logic includes a random number generator, a comparator, and alogic operator. The random number generator is configured to generate arandom number. The comparator is configured to compare the identifieddrop probability to the random number. The logic operator is configuredto perform a logical operation on a result of the comparison and asignal that indicates whether the identified drop probability is greaterthan zero and output, based on the logical operation, a decision signalthat indicates whether to drop data from one of the queues.

BRIEF DESCRIPTION OF THE DRAWINGS

The accompanying drawings, which are incorporated in and constitute apart of this specification, illustrate embodiments of the invention and,together with the description, explain the invention. In the drawings,

FIG. 1 is a diagram of an exemplary network device in which systems andmethods consistent with the principles of the invention may beimplemented;

FIG. 2 is an exemplary diagram of a packet forwarding engine (PFE) ofFIG. 1 according to an implementation consistent with the principles ofthe invention;

FIG. 3 is an exemplary diagram of a portion of the memory of FIG. 2according to an implementation consistent with the principles of theinvention;

FIG. 4 is an exemplary diagram of a portion of the packet informationmemory of FIG. 3 according to an implementation consistent with theprinciples of the invention;

FIG. 5 is an exemplary diagram of the queue control engine of FIG. 4according to an implementation consistent with the principles of theinvention;

FIG. 6 is an exemplary diagram of the oversubscription engine of FIG. 5according to an implementation consistent with the principles of theinvention;

FIG. 7 is an exemplary time line that facilitates measurement ofbandwidth use according to an implementation consistent with theprinciples of the invention;

FIG. 8 is a flowchart of exemplary oversubscription processing accordingto an implementation consistent with the principles of the invention;

FIGS. 9A-9D are exemplary diagrams that illustrate oversubscriptionaccording to an implementation consistent with the principles of theinvention;

FIG. 10 is an exemplary diagram of the drop engine of FIG. 5 accordingto an implementation consistent with the principles of the invention;

FIG. 11 is an exemplary graph of a drop profile consistent with theprinciples of the invention;

FIG. 12 is an exemplary diagram of the drop decision logic of FIG. 10according to an implementation consistent with the principles of theinvention;

FIGS. 13A and 13B are flowcharts of exemplary processing by the dropengine of FIG. 10 according to an implementation consistent with theprinciples of the invention; and

FIG. 14 is an exemplary diagram of queue selection using HIVec and LOVecvectors according to an implementation consistent with the principles ofthe invention.

DETAILED DESCRIPTION

The following detailed description of the invention refers to theaccompanying drawings. The same reference numbers in different drawingsmay identify the same or similar elements. Also, the following detaileddescription does not limit the invention. Instead, the scope of theinvention is defined by the appended claims and equivalents of therecited claim limitations.

Systems and methods consistent with the principles of the invention useone or more drop profiles, or drop tables, in determining theprobability of dropping data from a queue. The drop probability may thenbe further processed to make the ultimate drop decision. Such mechanismsprovide efficient data dropping compared to conventional mechanisms.

Exemplary Network Device Configuration

FIG. 1 is a diagram of an exemplary network device in which systems andmethods consistent with the principles of the invention may beimplemented. In this particular implementation, the network device takesthe form of a router 100. Router 100 may receive one or more packetstreams from a physical link, process the stream(s) to determinedestination information, and transmit the stream(s) on one or more linksin accordance with the destination information.

Router 100 may include a routing engine (RE) 110 and multiple packetforwarding engines (PFEs) 120 interconnected via a switch fabric 130.Switch fabric 130 may include one or more switching planes to facilitatecommunication between two or more of PFEs 120. In an implementationconsistent with the principles of the invention, each of the switchingplanes includes a single or multi-stage switch of crossbar elements.

RE 110 performs high level management functions for router 100. Forexample, RE 110 communicates with other networks and systems connectedto router 100 to exchange information regarding network topology. RE 110creates routing tables based on network topology information, createsforwarding tables based on the routing tables, and sends the forwardingtables to PFEs 120. PFEs 120 use the forwarding tables to perform routelookup for incoming packets. RE 110 also performs other general controland monitoring functions for router 100.

Each of PFEs 120 connects to RE 110 and switch fabric 130. PFEs 120receive packets on physical links connected to a network, such as a widearea network (WAN), a local area network (LAN), etc. Each physical linkcould be one of many types of transport media, such as optical fiber orEthernet cable. The packets on the physical link are formatted accordingto one of several protocols, such as the synchronous optical network(SONET) standard or Ethernet.

FIG. 2 is an exemplary diagram of a PFE 120 according to animplementation consistent with the principles of the invention. PFE 120may include two packet processors 210 and 220, each connected to amemory system 230 and RE 110. Packet processors 210 and 220 communicatewith RE 110 to exchange routing-related information. For example, packetprocessors 210 and 220 may receive forwarding tables from RE 110, and RE110 may receive routing information from packet processor 210 that isreceived over the physical link. RE 110 may also send routing-relatedinformation to packet processor 210 for transmission over the physicallink.

Packet processor 210 connects to one or more physical links. Packetprocessor 210 may process packets received from the incoming physicallinks and prepare packets for transmission on the outgoing physicallinks. For example, packet processor 210 may perform route lookup basedon packet header information to determine destination information forthe packets. For packets received from the links, packet processor 210may store data in memory system 230. For packets to be transmitted onthe links, packet processor 210 may read data from memory system 230.

Packet processor 220 connects to switch fabric 130. Packet processor 220may process packets received from switch fabric 130 and prepare packetsfor transmission to switch fabric 130. For packets received from switchfabric 130, packet processor 220 may store data in memory system 230.For packets to be transmitted to switch fabric 130, packet processor 220may read data from memory system 230.

Packet processors 210 and 220 may store packet data and other packetinformation, such as control and/or address information, within separateportions of memory system 230. FIG. 3 is an exemplary diagram of aportion of memory system 230 according to an implementation consistentwith the principles of the invention. In FIG. 3, memory system 230includes a data memory system 310 and a packet information memory system320. Data memory system 310 may store the data from a packet, possiblyin non-contiguous locations. Packet information memory system 320 maystore the corresponding packet information in queues based on, forexample, the packet stream to which the packet information corresponds.Other information, such as destination information and type of service(TOS) parameters for the packet, may be used in determining theparticular queue(s) in which to store the packet information.

FIG. 4 is an exemplary diagram of a portion of packet information memorysystem 320 according to an implementation consistent with the principlesof the invention. In FIG. 4, packet information memory system 320includes queues 410, dequeue engine 420, and queue control engine 430.In addition, memory system 320 may include an enqueue engine (not shown)that stores data in queues 410.

Packet information memory system 320 may concurrently store packetinformation corresponding to multiple, independent packet streams. In animplementation consistent with the principles of the invention, memorysystem 320 may contain separate queues 410, dequeue engines 420, andqueue control engines 430 corresponding to each of the packet streams.In other implementations, dequeue engine 420 and queue control engine430 may correspond to multiple streams.

Queues 410 may include a group of first-in, first-out (FIFO) buffersthat corresponds to a single stream. Other queues (not shown) may beprovided for other packet streams. Queues 410 share the bandwidth of asingle packet stream. In one implementation, each of queues 410 isallocated a static amount of packet information memory system 320 atconfiguration time. The amount of packet information memory system 320allocated to a particular queue may be determined based on factors, suchas the round trip time (Rtt), delay, and bandwidth associated with thestream, that minimize the chance that the queue will overflow.

Each of queues 410 may have three parameters associated with it: aweight between 0 and 1, a priority PR parameter that is either HI or LO,and a rate-control RC parameter that is either ON or OFF. A queue'sweight determines the fraction of the stream's bandwidth B that isstatically allocated to the queue. For a queue with weight w, thestatically allocated bandwidth sba is equal to w*B. The sum of theweights of the queues (e.g., queues 410) for a stream equal one. Inother words, the entire bandwidth of a stream is allocated to the queuesassociated with that stream.

The PR parameter specifies which of two priority levels (HI or LO) isassociated with a queue. In other implementations, there may be morethan two priority levels. Queues 410 associated with a HI priority maybe serviced before queues 410 associated with a LO priority. Queues 410at the same priority level may, for example, be serviced in a roundrobin manner.

The RC parameter determines whether a queue is allowed to oversubscribe(i.e., output more packet information than its statically allocatedbandwidth). If RC is OFF, then the queue is permitted to send up to thestream bandwidth B (the total bandwidth for the stream). If RC is ON,then the queue is rate controlled and not permitted to send more thanits statically allocated bandwidth sba.

Each of queues 410 is allocated a particular portion of data memorysystem 310 that stores packet data corresponding to the packetinformation stored by the queue. The size of the portion of data memorysystem 310 allocated to a particular queue (referred to as the staticmemory allocated sma) may be determined based on the stream's staticbandwidth. For example, the sma may be defined as the round trip time(Rtt) multiplied by the statically allocated bandwidth sba. Thestatically allocated bandwidth sba was defined above. In anotherimplementation, the sma may also take into account the speed of thestream.

The bandwidth allocated to a stream is fixed at B even though differentqueues within the stream may have dynamically changing bandwidthutilization, as will be described below. The stream itself never needsmore than Rtt (round trip time, which is defined as the maximum timeallowed for a packet to travel from the source to the destination andsend an acknowledgement back)*B of data memory system 310. This amountof data memory system 310 may be denoted by MA.

A delay bandwidth buffer is an amount of packet information memorysystem 320 equal to the network round trip time (Rtt) multiplied by thesum of the bandwidths of the output interfaces. An efficient way toallocate the delay bandwidth buffer is to share it dynamically amongqueues across all output interfaces.

Dequeue engine 420 may include logic that dequeues packet informationfrom queues 410. The order in which the streams are examined by dequeueengine 420 is referred to as the service discipline. For example, theservice discipline may include round robin or time division multiplexingtechniques. For each examination of a stream, dequeue engine 420 mayselect one of queues 410 and dequeue packet information from it. Toselect the queue, dequeue engine 420 may use the queue parameters w, PR,and RC. For each dequeue operation, the corresponding packet data indata memory system 310 may be read out and processed.

Queue control engine 430 may dynamically control the amount of datamemory system 310 used by each queue. Since the total bandwidth for thestream is B, queue control engine 430 effectively controls the totalamount of data memory system 310 used by queues 410 in a stream so thatit does not exceed MA. The memory is allocated at the time the packet isreceived and reclaimed either by a drop process if the queue hasexceeded its allocation (static and dynamic) or by a dequeue processwhen the packet is transmitted on a link.

FIG. 5 is an exemplary diagram of queue control engine 430 according toan implementation consistent with the principles of the invention. Queuecontrol engine 430 may include oversubscription engine 510 and dropengine 520. Oversubscription engine 510 may control whether any ofqueues 410 are permitted to output more packet information than theirstatically allocated bandwidth. Drop engine 520 may control whether todrop packet information from any of queues 410. Oversubscription engine510 and drop engine 520 will be described in more detail below. Whilethese engines are shown as separate, they may be integrated into asingle engine or may otherwise share data between them (connection notshown).

Oversubscription Engine

FIG. 6 is an exemplary diagram of oversubscription engine 510 accordingto an implementation consistent with the principles of the invention.Oversubscription engine 510 may include bandwidth used random accessmemory (RAM) 610, average bandwidth used RAM 620, timer 630, and controllogic 640. In an alternate implementation, bandwidth used RAM 610 andaverage bandwidth used RAM 620 are registers implemented within one ormore memory devices, such as a flip-flop.

Control logic 640 may include logic that coordinates or facilitates theoperation of the components of oversubscription engine 510. For example,control logic 640 may perform calculations, write or read data to orfrom the RAMs, or simply pass information between components ofoversubscription engine 510.

Bandwidth used RAM 610 may include multiple entries, such as one entryper queue. Each of the entries may store a variable that represents theinstantaneous amount of bandwidth used (bs) by the queue during a timeinterval (Ta). When packet information is dequeued by dequeue engine 420during the time interval Ta, the bs value may be incremented by thelength of the corresponding packet. The bs value may be reset atperiodic times identified by timer 630, such as the beginning or end ofa time interval.

Average bandwidth used RAM 620 may include multiple entries, such as oneentry per queue. Each of the entries may store data that represents atime-averaged measurement of the bandwidth used by the queue (bu) ascomputed during the time interval Ta. For example, the time-averagedmeasurement may be determined using an exponential weighted averagingwith a decay coefficient chosen to make the computation as efficient aspossible (e.g., two adds and a shift per time step). The weights in suchan exponential weighted averaging function may be programmable.

FIG. 7 is an exemplary time line that facilitates measurement ofbandwidth use according to an implementation consistent with theprinciples of the invention. The units of bu are bytes/time-step. Letbu[i] be the value of the average bandwidth used as computed in timestep i. Let bs[i] be the number of bytes sent by the queue in time stepi and n be an integer that determines the decay coefficient (1−2^(−n)).By expanding the recursion starting at bu[i]:bu[i]=bu[i−1]+2^(−n)(bs[i]−bu[i−1])bu[i]=bu[i−1]*(1−2^(−n))+bs[i]*2^(−n)Substituting r=(1−2^(−n)), the equation becomes:

$\begin{matrix}{{{bu}\lbrack i\rbrack} = {{{{bu}\left\lbrack {i - 1} \right\rbrack}*r} + {{{bs}\lbrack i\rbrack}*\left( {1 - r} \right)}}} \\{= {{\left( {{{{bu}\left\lbrack {i - 2} \right\rbrack}*r} + {{{bs}\left\lbrack {i - 1} \right\rbrack}*\left( {1 - r} \right)}} \right)*r} + {{{bs}\lbrack i\rbrack}*\left( {1 - r} \right)}}} \\{= {\left( {1 - r} \right)*{\left( {{{bs}\lbrack i\rbrack} + {{{bs}\left\lbrack {i - 1} \right\rbrack}*r} + {{{bs}\left\lbrack {i - 2} \right\rbrack}*r^{2}} + {{{bs}\left\lbrack {i - 3} \right\rbrack}*r^{3}} + \ldots} \right).}}}\end{matrix}$As can be seen, the bandwidth used by a queue is a function of thebandwidth used by the queue in all the previous time intervals.

The final equation is an exponential weighted average with coefficientr. To get an idea of how many steps k it takes for the coefficientsr^(k) to become “small,” the following binomial expansion may be used:(1−2^(n))^(k)˜1−k*2^(−n)as long as k*2^(−n) is much less than 1. This means that as long as k issignificantly less than 2^(n), the terms are taken into account almostfully, but as k approaches 2^(n), r^(k) will start to drop off rapidlyand so the terms become less and less significant.

Returning to FIG. 6, timer 630 may include a programmable registerand/or counter that identifies the times at which time averaging may beperformed to generate bu. At the beginning of a programmable timeinterval Ta, the bs value in bandwidth used RAM 610 may be reset tozero. At the end of the time interval Ta, the current bs value may beread from bandwidth used RAM 610 and the average bu value (computed inthe previous time interval) may be read from average bandwidth used RAM620. A weighted averaging function may then be performed on thesevalues, such as the one described above, and the resultant value may bestored in average bandwidth used RAM 620. The bs value in bandwidth usedRAM 610 may then be reset to zero again at the beginning of the nexttime interval Ta+1 and the process repeated.

Control logic 640 may reallocate bandwidth to permit oversubscriptionbased on the bandwidth actually used by queues 410. For example, controllogic 640 may determine the average bandwidth bu used by each of queues410 and reallocate bandwidth to certain ones of queues 410 if the queuespermit oversubscription based on the RC parameter associated with thequeues.

FIG. 8 is a flowchart of exemplary oversubscription processing accordingto an implementation consistent with the principles of the invention. Inthis implementation, control logic 640 performs oversubscriptionprocessing at the programmable time interval determined by timer 630. Inother implementations, control logic 640 performs this processing atother times, which may be based on certain criteria, such as trafficflow-related criteria.

Processing may begin with control logic 640 determining theinstantaneous bandwidth bs used by queues 410 (act 810). To make thisdetermination, control logic 640 may read bs values, corresponding toqueues 410, from bandwidth used RAM 610. As described above, the bsvalue for a queue may be calculated based on the length of the packet(s)corresponding to the packet information dequeued by the queue during atime interval.

Control logic 640 may use the bs values and the bu values from theprevious time interval to determine the average bandwidth bu used byqueues 410 during the current time interval (act 820). To make thisdetermination, control logic 640 may take a time-averaged measurement ofthe bandwidth used by performing an exponential weighted averaging witha decay coefficient chosen to make the computation as efficient aspossible (e.g., two adds and a shift per time step). A method fordetermining the average bandwidth bu has been described above.

Control logic 640 may use the average bandwidth bu to reallocatebandwidth to queues 410 (act 830). For example, control logic 640 mayidentify which of queues 410 permit oversubscription based on the RCparameters associated with queues 410. If the average bandwidth bu usedby a queue is less than its statically allocated bandwidth, the unusedportion of the bandwidth may be divided among the queues that arepermitted to oversubscribe and need extra bandwidth. Any queue that isnot permitted to oversubscribe cannot use any of the unused bandwidth.

FIGS. 9A-9D are exemplary diagrams that illustrate oversubscriptionaccording to an implementation consistent with the principles of theinvention. Assume that there are four queues Q0-Q3 that share a stream'sbandwidth B. Assume further that Q0 has a weight of 0.7 and Q1-Q3 eachhas a weight of 0.1. In other words, Q0 is allocated 70% of thebandwidth B and each of Q1-Q3 is allocated 10% of the bandwidth B. FIG.9A illustrates such a configuration.

Assume further that RC is OFF for Q0-Q2 and ON for Q3. Therefore, Q0-Q2are permitted to oversubscribe and Q3 is rate controlled and notpermitted to oversubscribe. Assume that Q0 uses almost none of thebandwidth allocated to it. In this case, Q1 and Q2 may share thebandwidth unused by Q0. Accordingly, 0% of the bandwidth B is used byQ0, 45% is dynamically reallocated to each of Q1 and Q2, and 10% remainsallocated to Q3. FIG. 9B illustrates such a configuration.

Assume at some later point in time that control logic 640 determinesthat traffic on Q0 increases based on the average bandwidth bu used byQ0, such that Q0 requires 40% of the bandwidth B. In this case, Q0reclaims some of its bandwidth from Q1 and Q2. Since Q0 needs 40% of thebandwidth B, the remaining 30% unused by Q0 is divided between Q1 andQ2. Therefore, 40% of the bandwidth B is dynamically reallocated to Q0,25% is dynamically reallocated to each of Q1 and Q2, and 10% remainsallocated to Q3. FIG. 9C illustrates such a configuration. Thereallocation of bandwidth is equal between Q1 and Q2 as long as they canuse that bandwidth. If Q1 has just enough traffic to use 15% of theoverall bandwidth, then Q2 will get 35% of the total bandwidth. FIG. 9Dillustrates such a configuration.

As can be seen from the foregoing, the bandwidth allocated to queues 410in a given time interval is related to both the queues' staticallyallocated bandwidth and the bandwidth used by the queues. This dynamicallocation process may be summarized as: (1) allocating the availablebandwidth in proportion to the queues' statically allocated bandwidth;and (2) distributing the excess bandwidth among active queues inproportion to their excess bandwidths used in previous time intervals.

Drop Engine

Drop engine 520 may include RED logic that controls the amount of datamemory system 310 used by queues 410 such that the average latencythrough queues 410 remains small even in the presence of congestion. Thedrop process is profiled in the sense that the probability of a packetinformation drop is not fixed, but is a user-specifiable function of howcongested a queue is. Generally, the drop process may make its dropdecision based on the ratio between the current queue length and themaximum permissible queue length.

Drop engine 520 makes its drop decision based on the state of queues410, not on the state of the stream. Drop engine 520 may operate in around robin fashion on all of the active queues. By design, it has ahigher probability of examining more active queues rather than inactivequeues to keep up with the data rate of a quickly-filling queue.

The drop decision is made at the head of queues 410 rather than at thetail, as in conventional systems. A benefit of dropping at the head ofqueues 410 is that congestion is signaled earlier to traffic sources,thereby providing tighter latency control. By comparison, a tail dropcan result in the congestion signal being delayed by as much as Rttcompared to a head drop because a more recent packet is being droppedwhose response time-out will expire later. Also, if queues 410 areallowed to oversubscribe and use more memory than allocated to them,then head drop provides a way to cut back excess memory use when aqueue's bandwidth suddenly drops because a previously inactive queue hasstarted to use its share of the bandwidth again.

FIG. 10 is an exemplary diagram of drop engine 520 according to animplementation consistent with the principles of the invention. Dropengine 520 may include static memory allocated RAM 1010, memory used RAM1020, pending RED visit (PRV) RAM 1030, indexing logic 1040, dropprofile 1050, drop decision logic 1060, and control logic 1070. In analternate implementation, static allocated RAM 1010, memory used RAM1020, and PRV RAM 1030 are registers implemented within one or morememory devices, such as a flip-flop.

Control logic 1070 may include logic that coordinates or facilitates theoperation of the components of drop engine 520. For example, controllogic 1070 may perform calculations, write or read to or from the RAMs,or simply pass information between components of drop engine 520.

Static memory allocated RAM 1010 may include multiple entries, such asone entry per queue. Each of the entries may store the variable sma,corresponding to the queue, that identifies the amount of data memorysystem 310 that should be made available to the queue (in the case whereit is not allowed to oversubscribe due to RC being set or all of theother queues using their allocated bandwidth and, thereby, sparing nounused bandwidth). As defined above, sma is defined as the round triptime Rtt multiplied by the statically allocated bandwidth sba.

Memory used RAM 1020 may include multiple entries, such as one entry perqueue. Each of the entries may store a variable mu that represents theamount of data memory system 310 actually being used by the queue.Storage space within data memory system 310 may be allocated dynamicallyat the time a packet is received and reclaimed at some time after thepacket is transmitted by router 100. The variable mu, which counts bytesor cells (e.g., 64 byte data blocks) of data, may be used to track theamount of data memory system 310 used by the queue. When packetinformation is enqueued, the mu value may be incremented by the lengthof the corresponding packet. When packet information is dequeued bydequeue engine 420 or dropped by drop engine 430, the mu value may bedecremented by the length of the corresponding packet.

PRV RAM 1030 may include multiple entries, such as one entry per queue.Each of the entries may store a variable prv that controls how manytimes the queue will be examined by drop engine 430. When packetinformation is enqueued, the prv value may be incremented by one. Whenpacket information is dequeued by dequeue engine 420 or an examinationof the queue by drop engine 430 occurs, the prv value may be decrementedby one, if the prv value is greater than zero. The goal is to allow dropengine 430 to visit each packet at the head of the queue just once. Aqueue visited once may not be visited again unless the packet justvisited got dropped or the packet gets dequeued by dequeue engine 420.

Indexing logic 1040 may include logic for creating an index into dropprofile 1050. Drop profile 1050 may include a memory that includesmultiple addressable entries. Each of the entries may store a value thatindicates the probability of a drop. For example, assume that dropprofile 1050 includes 64 entries that are addressable by a six bitaddress (or index). In an implementation consistent with the principlesof the invention, each of the entries includes an eight bit numberrepresenting a drop probability. The drop probability may always begreater than or equal to zero.

The relationship of drop probability to index may be expressed as amonotonically non-decreasing function. FIG. 11 is an exemplary graph ofa drop profile consistent with the principles of the invention. As shownby the graph, the drop profile is a monotonically non-decreasingfunction with the drop probability of zero at index zero and the dropprobability of one at index 63. In one implementation, an entry value ofzero may be used to represent never drop, an entry value of 255 may beused to represent always drop, and entry values in between zero and 255may represent a drop probability according to the relation:probability of drop=(entry value)/256.

Returning to FIG. 10, indexing logic 1040 may generate the index intodrop profile 1050 using, for example, the expression:index=(mu/MAX)*64,where MAX is the maximum of the values of sma (static memory allocated)and dma (dynamic memory allocated, which is the amount of data memorysystem 310 that should be made available to a particular queue and isdefined as the average bandwidth used bu*(Rtt/Ta)). This may beconsidered a dynamic index because its value may change based on changesto the variable dma. In an alternate implementation, indexing logic 1040may generate a static index using, for example, the expression:index=(mu/sma)*64.This may be considered a static index because the value of sma will notchange. According to an implementation consistent with the principles ofthe invention, the index generated is a six bit value. In otherimplementations, other size indexes are possible.

If the situation occurs where mu becomes greater than MAX, then theratio of mu/MAX results in a value larger than one. When this happens,the index may contain a value that points to somewhere outside dropprofile 1050. In this case, drop decision logic 1060 may consider this amust drop situation and drop the packet unless the packet contains anattribute, such as a keep alive attribute, that indicates that thepacket should not be dropped.

In some situations, an index threshold may be used. As shown in FIG. 11,the drop profile is a monotonically non-decreasing function with thedrop probability of zero at index zero and the drop probability of oneat index 63. The index threshold may be set, such that if the indexvalue generated by indexing logic 1040 is less than or equal to thethreshold value, the lookup in drop profile 1050 may be skipped and thepacket not dropped.

In another implementation consistent with the principles of theinvention, packet attributes, such as the packet's Transmission ControlProtocol (TCP) and/or Packet Level Protocol (PLP), may be used inconjunction with the index as an address into drop profile 1050. In thiscase, drop profile 1050 may include multiple profile tables, each havingmultiple addressable entries. The packet attributes may be used toselect among the profile tables. For example, two bits representing theTCP and PLP of a packet may be used to select among four differentprofile tables in drop profile 1050. The index may then be used toidentify an entry within the selected table. In this way, a certain setof attributes extracted from the packets may be used to perform anintelligent drop.

Drop decision logic 1060 may include logic that makes the ultimate dropdecision based on the drop probability in drop profile 1050 or otherfactors as described above. In other words, drop decision logic 1060translates the drop probability into a drop decision for the packetinformation examined by drop engine 520.

FIG. 12 is an exemplary diagram of drop decision logic 1060 according toan implementation consistent with the principles of the invention. Dropdecision logic 1060 includes random number generator 1210, comparator1220, and AND gate 1230. Random number generator 1210 may include apseudo random number generator, such as a linear feedback shift registerthat creates a pseudo random number that has a uniform distributionbetween zero and one. Random number generator 1210 may generate a randomnumber that has the same number of bits as the drop probability valuefrom drop profile 1050. To increase randomness, however, random numbergenerator 1210 may generate a random number that has a greater number ofbits as the drop probability value from drop profile 1050.

Random number generator 1210 may implement functions as represented bythe following:

lfsr_galois(int state) { int x0, x5, x12; if (0x0001 & state) { state =state>> 1; state = state{circumflex over ( )}0x8000{circumflex over( )}0x0800{circumflex over ( )}0x0010; } else state = state >> 1;return(state); }to generate the random number.

Comparator 1220 may compare the random number from random numbergenerator 1210 to the drop probability value from drop profile 1050. ANDgate 1230 may perform a logical AND operation on the result of thecomparison and a “DO NOT DROP” signal, which may be generated based onthe presence or absence of an attribute, such as a keep alive attribute,that may be extracted from the packet. In an implementation consistentwith the principles of the invention, comparator 1220 and AND gate 1230may be designed to output a drop decision to: (1) drop the packetinformation if the random number is less than the drop probability valueand the DO NOT DROP signal indicates that the packet information may bedropped; (2) not drop the packet information if the random number isless than the drop probability value and the DO NOT DROP signalindicates that the packet information should not be dropped; and (3) notdrop the packet information if the random number is not less than thedrop probability value regardless of the value of the DO NOT DROPsignal.

FIGS. 13A and 13B are flowcharts of exemplary processing by drop engine520 according to an implementation consistent with the principles of theinvention. Drop engine 520 may operate in parallel to dequeue engine420. Therefore, packet information memory system 320 may includemechanisms to arbitrate between drop engine 520 and dequeue engine 420competing for the same resource (i.e., the same packet information atthe head of a queue). In implementations consistent with the principlesof the invention, drop engine 520 and dequeue engine 420 may bepermitted to access different packet information on the same queue.

Optionally, drop engine 520 may select a stream to examine (act 1305)(FIG. 13A). For example, drop engine 520 may use a round robin techniqueor another technique to determine which of the possible streams toexamine next. Alternatively, in another implementation, drop engine 520may consider all of the queues in a round robin manner without firstselecting a stream. In this case, act 1305 may be unnecessary.

Once a stream has been selected, if necessary, drop engine 520 mayselect a queue to examine based on, for example, the queues' prv values(act 1310). The drop engine 520 may use round robin arbitration toselect the next queue with a prv value greater than zero.

Alternatively, drop engine 520 may construct two bit vectors (HIVec andLOVec) and perform a round robin over these vectors to select the nextqueue to examine. The HIVec and LOVec vectors may be defined as follows:

for queue_(i), where i = 0 to total number of queues: if (mu_(i) >MAX_(i)), HIVec[i] = 1; else { if (mu_(i) < (MAX_(i)/X)), LOVec[i] = 0;else LOVec[i] = (prv[i] > 0) }where X is an integer, such as 16. This conserves drop engine 520examinations of a queue when mu is small compared to MAX and forces dropengine 520 examinations when mu exceeds MAX. When mu is very smallcompared to MAX/X, the drop probability will be small. Keeping LOVecreset allows drop engine 520 to visit other more active queues.

FIG. 14 is an exemplary diagram of queue selection using the HIVec andLOVec vectors according to an implementation consistent with theprinciples of the invention. Drop engine 520 may use the two bit vectorsHIVec and LOVec to select the next queue to examine. Drop engine 520 maybegin searching HIVec at HIPtr+1 looking for the first queue i that hasHIVec[i]=1. If there is no such queue, then drop engine 520 may searchLOVec starting at LOPtr+1 looking for the first queue i that hasLOVec[i]=1.

Returning to FIG. 13A, when drop engine 520 finds a queue i, itdetermines the variable dma (i.e., the average bandwidth used bu*Rtt)and, from it, the variable MAX(act 1315). As described above, MAX isdefined as the maximum of the values of sma from static memory allocatedRAM 1010 and dma. From MAX, drop engine 520 generates an index into dropprofile 1050 (act 1320). As described above, the index may be definedas: mu/MAX*64. In this case, the generated index may be a six bitnumber. If the ratio of mu/MAX results in a value greater than one, thendrop engine 520 may drop the packet (if the packet does not contain anattribute, such as a keep alive attribute). If the resulting index valueis below some threshold, drop engine 520 may bypass the drop profilelookup and not drop the packet.

If an index threshold (T/H) is used, drop engine 520 may compare mu/MAXto the threshold to determine whether mu/MAX is less than or equal tothe threshold (act 1325). If mu/MAX is less than or equal to thethreshold, drop engine 520 may mark the packet as not to be dropped (act1330). Marking may be done by simply setting a bit associated with thepacket or by not dropping packet information from the queue.

If mu/MAX is greater than the threshold, drop engine 520 may determinewhether mu/MAX is greater than or equal to one (act 1335). If so, thendrop engine 520 may determine whether the packet includes a packetattribute, such as a keep alive attribute, that indicates that it is notto be dropped (act 1340). The presence or absence of this packetattribute may be used to generate the DO NOT DROP signal. If the DO NOTDROP signal indicates that the packet should not be dropped, then dropengine 520 may mark the packet as not to be dropped (act 1345).Otherwise, drop engine 520 may mark the packet for dropping (act 1350).

If mu/MAX is less than one, however, drop engine 520 may use the indexto access drop profile 1050 and obtain a drop probability (act 1355)(FIG. 13B). If drop profile 1050 contains more than one profile table,drop engine 520 may use packet attributes to select one of the profiletables. Drop engine 520 may then use the index as an address into theselected profile table and read a drop probability value therefrom.

Drop engine 520 may determine a drop decision by comparing the dropprobability value to a random number (acts 1360 and 1365). The randomnumber may be generated by random number generator 1210. If the randomnumber is less than the drop probability value, drop engine 520 maydetermine whether the packet includes a packet attribute, such as a keepalive attribute, that indicates that it is not to be dropped (act 1370).The presence or absence of this packet attribute may be used to generatethe DO NOT DROP signal.

If the random number is less than the drop probability value and the DONOT DROP signal indicates that the packet may be dropped, then dropengine 520 may mark the packet for dropping (act 1375). If the DO NOTDROP signal, in this case, indicates that the packet is not to bedropped, then drop engine 520 may mark the packet as not to be dropped(act 1380). If the random number is not less than the drop probabilityvalue, regardless of the value of the DO NOT DROP signal, then dropengine 520 may mark the packet as not to be dropped (act 1380). Markingmay be done by simply setting a bit associated with the packet or bydropping or not dropping packet information from the queue.

In response to a decision to drop, drop engine 520 may remove theassociated packet information from the queue. Alternatively, the queuemay discard the packet information itself when instructed by drop engine520.

CONCLUSION

Systems and methods, consistent with the principles of the invention,efficiently determine whether to drop data from a queue. The dropdecision may be based on one or more drop profiles that indicate theprobability that the data will be dropped. The drop probability may befurther processed to generate the ultimate drop decision.

The foregoing description of preferred embodiments of the presentinvention provides illustration and description, but is not intended tobe exhaustive or to limit the invention to the precise form disclosed.Modifications and variations are possible in light of the aboveteachings or may be acquired from practice of the invention. Forexample, dequeue engine 420 and queue control engine 430 have beendescribed as separate components. In other implementations consistentwith the principles of the invention, the engines may be integrated intoa single engine that both dequeues and drops packet information.

Also, while some memory elements have been described as RAMs, othertypes of memory devices may be used in other implementations consistentwith the principles of the invention.

Certain portions of the invention have been described as “logic” thatperforms one or more functions. This logic may include hardware, such asan application specific integrated circuit or a field programmable gatearray, software, or a combination of hardware and software.

No element, act, or instruction used in the description of the presentapplication should be construed as critical or essential to theinvention unless explicitly described as such. Also, as used herein, thearticle “a” is intended to include one or more items. Where only oneitem is intended, the term “one” or similar language is used. The scopeof the invention is defined by the claims and their equivalents.

1. A system for selectively dropping data from a queue, comprising: aplurality of queues configured to temporarily store data; and a dropengine configured to select one of the queues to examine, the dropengine comprising: a drop table configured to store a plurality of dropprobabilities, indexing logic configured to generate an index into thedrop table to identify one of the drop probabilities, wherein theindexing logic is configured to: determine a static amount of memoryallocated to the examined queue, determine an amount of memory used bythe examined queue, and determine the index into the drop table based onthe static amount of memory allocated to the examined queue and theamount of memory used by the examined queue, and drop decision logicconfigured to determine whether to drop data from a head of the examinedqueue based on the identified drop probability.
 2. The system of claim1, wherein the indexing logic is configured to: generate the index intothe drop table based on an amount of memory used by the examined queue,and identify one of the drop probabilities in the drop table using thegenerated index.
 3. The system of claim 1, wherein when determining theindex, the indexing logic is configured to: generate the index based ona ratio of the amount of memory used by the examined queue to a maximumof the static amount of memory allocated to the examined queue or theamount of memory that should be made available to the examined queue. 4.The system of claim 1, wherein the drop table includes: a plurality ofdrop tables each of which is configured to store a plurality of dropprobabilities.
 5. The system of claim 4, wherein the indexing logic isfurther configured to: select one of the drop tables, and identify oneof the drop probabilities in the selected drop table using the generatedindex.
 6. The system of claim 5, wherein when selecting one of the droptables, the indexing logic is configured to: use one or more attributesof the data to select among the drop tables.
 7. The system of claim 6,wherein the attributes include one or more of a Transmission ControlProtocol or a Packet Level Protocol relating to the data.
 8. The systemof claim 1, wherein the drop decision logic includes: a random numbergenerator configured to generate a random number, and a comparatorconfigured to: compare the identified drop probability to the randomnumber, and generate a drop decision based on a result of thecomparison.
 9. The system of claim 8, wherein the random numbergenerator is a pseudo random number generator.
 10. The system of claim8, wherein the random number generator is a linear feedback shiftregister.
 11. The system of claim 8, wherein the random number has asame number of bits as a number of bits in the identified dropprobability.
 12. The system of claim 8, wherein the random number has agreater number of bits than a number of bits in the identified dropprobability.
 13. The system of claim 8, wherein the drop decision logicfurther includes: a logic operator configured to: perform a logicaloperation on the result of the comparison and a signal based on anattribute extracted from the data, and output, based on the logicaloperation, a decision signal that indicates whether to drop data fromthe examined queue.
 14. The system of claim 13, wherein the logicoperator is an AND gate.
 15. The system of claim 1, wherein the dropdecision logic is configured to: determine whether to drop data from theexamined queue based on the identified drop probability and otherinformation including information extracted from the data.
 16. Thesystem of claim 15, wherein the information includes an attribute thatindicates that the data should not be dropped.
 17. The system of claim1, wherein an index threshold is established; and wherein the dropdecision logic is configured to: determine not to drop the data when theindex generated by the indexing logic is below the index threshold. 18.A system for selectively dropping data from a queue, comprising: aplurality of queues configured to temporarily store data; and a dropengine configured to select one of the queues to examine, the dropengine comprising: a drop table configured to store a plurality of dropprobabilities, indexing logic configured to generate an index into thedrop table to identify one of the drop probabilities, and drop decisionlogic configured to determine whether to drop data from a head of theexamined queue based on the identified drop probability, wherein thedrop probability is based on a ratio of an amount of memory being usedby the examined queue to a maximum of a static amount of memoryallocated to the examined queue or an amount of memory that should bemade available to the examined queue.
 19. The system of claim 18,wherein the drop decision logic is configured to: identify the data fordropping when the amount of memory being used by the examined queue isgreater than the maximum of the static amount of memory allocated to theexamined queue or the amount of memory that should be made available tothe examined queue.
 20. A system for selectively dropping data from aqueue, comprising: a plurality of queues configured to temporarily storedata; and a drop engine configured to select one of the queues toexamine, the drop engine comprising: a drop table configured to store aplurality of drop probabilities, indexing logic configured to generatean index into the drop table to identify one of the drop probabilities,and drop decision logic configured to determine whether to drop datafrom a head of the examined queue based on the identified dropprobability, wherein the drop probability is based on a ratio of anamount of memory being used by the examined queue to a static amount ofmemory allocated to the examined queue.
 21. A method for selectivelydropping data from each of a plurality of queues that temporarily storedata, comprising: selecting one of the queues to examine; providing adrop table that stores a plurality of drop probabilities; generating anindex into the drop table to identify one of the drop probabilities forthe examined queue, wherein the generating the index includes:determining a static amount of memory allocated to the examined queue,determining an amount of memory used by the examined queue, anddetermining the index into the drop table based on the static amount ofmemory allocated to the examined queue and the amount of memory used bythe examined queue; and determining whether to drop data from a head ofthe examined queue based on the identified drop probability.
 22. Themethod of claim 21, wherein the generating an index includes:determining an amount of memory used by the examined queue, generatingthe index into the drop table based on the determined amount of memory,and identifying one of the drop probabilities in the drop table usingthe generated index.
 23. The method of claim 21, wherein the determiningthe index includes: generating the index based on a ratio of the amountof memory used by the examined queue to a maximum of the static amountof memory allocated to the examined queue or the amount of memory thatshould be made available to the examined queue.
 24. The method of claim21, wherein the drop table includes a plurality of drop tables each ofwhich is configured to store a plurality of drop probabilities; andwherein the method further comprises: selecting one of the drop tables,and identifying one of the drop probabilities in the selected drop tableusing the generated index.
 25. The method of claim 24, wherein theselecting one of the drop tables includes: using one or more attributesof the data to select among the drop tables.
 26. The method of claim 25,wherein the attributes include one or more of a Transmission ControlProtocol or a Packet Level Protocol relating to the data.
 27. The methodof claim 21, wherein the determining whether to drop data from theexamined queue includes: generating a random number, comparing theidentified drop probability to the random number, and generating a dropdecision based on a result of the comparison.
 28. The method of claim27, wherein the random number has a same number of bits as theidentified drop probability.
 29. The method of claim 27, wherein therandom number has a greater number of bits than the identified dropprobability.
 30. The method of claim 27, wherein the determining whetherto drop data from the examined queue further includes: performing alogical operation on the result of the comparison and a signal based onan attribute extracted from the data, and outputting, based on thelogical operation, a decision signal that indicates whether to drop datafrom the examined queue.
 31. The method of claim 30, wherein theperforming a logical operation includes: ANDing the result of thecomparison and the signal that indicates whether the identified dropprobability is greater than zero.
 32. The method of claim 21, whereinthe determining whether to drop data includes: determining whether todrop the data from the examined queue based on the identified dropprobability and other information including information extracted fromthe data.
 33. The method of claim 21, wherein the information includesan attribute that indicates that the data should not be dropped.
 34. Themethod of claim 21, further comprising: establishing an index threshold;and wherein the determining whether to drop data includes: determiningnot to drop the data when the index is below the index threshold.
 35. Amethod for selectively dropping data from each of a plurality of queuesthat temporarily store data, comprising: selecting one of the queues toexamine; providing a drop table that stores a plurality of dropprobabilities; generating an index into the drop table to identify oneof the drop probabilities for the examined queue; and determiningwhether to drop data from a head of the examined queue based on theidentified drop probability, wherein the drop probability is based on aratio of an amount of memory being used by the examined queue to amaximum of a static amount of memory allocated to the examined queue oran amount of memory that should be made available to the examined queue.36. The method of claim 35, wherein the determining whether to drop dataincludes: identifying the data for dropping when the amount of memorybeing used by the examined queue is greater than the maximum of thestatic amount of memory allocated to the examined queue or the amount ofmemory that should be made available to the examined queue.
 37. A methodfor selectively dropping data from each of a plurality of queues thattemporarily store data, comprising: selecting one of the queues toexamine; providing a drop table that stores a plurality of dropprobabilities; generating an index into the drop table to identify oneof the drop probabilities for the examined queue; and determiningwhether to drop data from a head of the examined queue based on theidentified drop probability, wherein the identified drop probability isbased on a ratio of an amount of memory being used by the examined queueto a static amount of memory allocated to the examined queue.